In the present study we develop a Takagi-Sugeno (TS) fuzzy model of a concentric-tubes heat exchanger. The model is structured on fuzzy logic reasoning with sets of linguistic rules describing the dynamic characteristics of the thermal system. Using a system identification technique based on adaptive neural networks, the fuzzy rules are derived from experimental data of the flow rates and fluid temperatures in the heat exchanger. The accuracy of the resulting model is assessed by predicting the time-dependent response of the outlet hot- and cold-water temperatures under a step-change in the mass flow rate of the cold fluid. The results indicate that the TS fuzzy model is able to estimate the behavior of the physical system with very little predicting errors. Upon the basis of this empirical model, in the near future we will report on a control strategy for the regulation and tracking of the outlet temperatures in the heat exchanger.

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